Electricity Price Modelling for Turkey

  • Miray Hanım Yıldırım
  • Ayşe Özmen
  • Özlem Türker Bayrak
  • Gerhard Wilhelm Weber
Conference paper
Part of the Operations Research Proceedings book series (ORP)

Abstract

This paper presents customized models to predict next-day’s electricity price in short-term periods for Turkey’s electricity market. Turkey’s electricity market is evolving from a centralized approach to a competitive market. Fluctuations in the electricity consumption show that there are three periods; day, peak, and night. The approach proposed here is based on robust and continuous optimization techniques, which ensures achieving the optimum electricity price to minimize error in periodic price prediction. Commonly, next-day’s electricity prices are forecasted by using time series models, specifically dynamic regression model. Therefore electricity price prediction performance was compared with dynamic regression. Numerical results show that CMARS and RCMARS predicts the prices with 30% less error compared to dynamic regression.

Keywords

Root Mean Square Error Time Series Model Electricity Market Electricity Price Multivariate Adaptive Regression Spline 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Miray Hanım Yıldırım
    • 1
    • 2
  • Ayşe Özmen
    • 1
  • Özlem Türker Bayrak
    • 2
  • Gerhard Wilhelm Weber
    • 1
  1. 1.Inst. of Appl. Math.Middle East Technical Univ.AnkaraTurkey
  2. 2.Dept. of Industrial EngineeringÇankaya Univ.AnkaraTurkey

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